Multicolor labeling for cell identification in the C. Elegans Nervous system

用于线虫神经系统细胞识别的多色标记

• 批准号: 9548756
• 负责人: John Isaac Murray
• 金额: $ 20.19万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9548756
• 关键词: Ablation; Adult; Aging; Animals; Behavior; Brain; Brain imaging; Caenorhabditis elegans; Calcium; Cell Count; Cell Lineage; Cell Proliferation; Cell Shape; Cell physiology; Cells; Collection; Color; Complex; Computer software; Computing Methodologies; Databases; Defect; Development; Embryo; Embryonic Development; Embryonic Nervous System; Fluorescence; Functional Imaging; Future; Gene Expression; Genes; Genetic; Head; Image; Individual; Investigation; Label; Location; Locomotion; Maps; Measurement; Measures; Methods; Modeling; Morphology; Motor; Nematoda; Nerve; Nervous System Physiology; Nervous system structure; Neurons; Organism; Pathway interactions; Pattern; Phenotype; Population; Population Study; Positioning Attribute; Process; Property; Proteins; Resolution; Role; Specificity; Structure; Techniques; Technology; Testing; Three-Dimensional Imaging; Time; Tissues; Transgenic Organisms; blastomere structure; cell motility; cell type; connectome; experimental study; gene function; imaging Segmentation; imaging modality; imaging platform; improved; mutant; nerve stem cell; neural circuit; optical imaging; progenitor; promoter; relating to nervous system; tool

To understand how cells develop or function, it is important to study equivalent cells across individuals. Comparing a cell's fate between mutant and wild-type individuals can reveal how a gene regulates development. Similarly, combining information about a neuron's structure from one animal with functional recordings of its activity in another can reveal that neuron's contribution to a circuit. Comparing information across animals requires identifying cells by some combination of cell shape, position, gene expression and lineage. However, methods to identify cell fates in complex tissues are simplex, focusing on one or a small number of cell types at a time, making it hard to assess the behavior of the full population. We propose to develop multiplexed 3D multicolor fluorescent labeling and associated hardware and software to automate cell identification in live animals. In Aim 1 we will develop this approach in the nematode C. elegans because its invariant developmental lineage and known wiring of every neuron provides a powerful platform on which to build, test and validate this approach. In Aim 2 we will apply this to understand patterns of fate transformations across the entire organism in developmental mutants. Finally in Aim 3, we will use our labeling method to identify all neurons in the adult nerve ring (brain), and combine this with whole-brain imaging methods to map for the first time activity of every neuron onto the wiring diagram.

为了了解细胞如何发育或发挥功能，重要的是要研究个体之间的等效细胞。 比较突变体和野生型个体之间细胞的命运可以揭示基因如何调节 发展类似地，将来自一种动物的神经元结构的信息与功能信息相结合， 对另一个神经元活动的记录可以揭示该神经元对电路的贡献。比较信息 需要通过细胞形状、位置、基因表达和 脉然而，在复杂组织中鉴定细胞命运的方法是单一的，集中在一个或一个小的 细胞类型的数量，使得很难评估整个群体的行为。我们建议 开发多路复用3D多色荧光标记以及相关硬件和软件， 在活体动物中自动识别细胞。在目标1中，我们将在线虫C中开发这种方法。 因为它不变的发育谱系和已知的每个神经元的布线提供了一个强大的 平台上建立，测试和验证这种方法。在目标2中，我们将应用这一点来理解 发育突变体中整个生物体的命运转变。最后，在目标3中，我们将使用 一种标记方法，用于识别成人神经环（脑）中的所有神经元，并将其与全脑联合收割机相结合 成像方法首次将每个神经元的活动映射到接线图上。